FindDominantCells: Method for finding dominant cells according to (possibly multiple) n,k dominance rules.

Description

Supports functionality for grouping contributions according to holding variables, as well as calculating dominance in surveys with a given sampling weight. Two methods are implemented, depending on whether the sampling weights sum to total population. The parameter tauArgusDominance determines this. If FALSE, unweighted contributions are compared to weighted cell values. If TRUE, the method described in in the book "Statistical Disclosure Control" (Hundepool et al 2012, p. 151) is used.

Usage

FindDominantCells(
  x,
  inputnum,
  num,
  n,
  k,
  charVar_groups,
  samplingWeight,
  tauArgusDominance = FALSE,
  returnContrib = FALSE,
  maxContribution = NULL
)

Value

logical vector describing which publish-cells need to be suppressed.

Arguments

x: model matrix describing relationship between input and published cells
inputnum: vector of numeric contributions for each of the input records
num: vector of numeric values for each of the published cells
n: vector of integers describing n parameters in n,k rules. Must be same length as k parameter.
k: vector of numeric values describing k parameters in n,k rules, where percentages are described as numbers less than 100. Must be same length as n parameter.
charVar_groups: vector describing which input records should be grouped
samplingWeight: vector of sampling weights associated to input records
tauArgusDominance: logical value, default FALSE. determines how to handle sampling weights in the dominance rule (see details).
returnContrib: logical value, default FALSE. If TRUE return value is the percentage of the first n contributors
maxContribution: Possible precalculated output from MaxContribution as input. To speed up.